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Topologically assisted optimization for rotor design.
- Source :
-
Physics of Fluids . May2023, Vol. 35 Issue 5, p1-13. 13p. - Publication Year :
- 2023
-
Abstract
- We develop and apply a novel shape optimization exemplified for a two-blade rotor with respect to the figure of merit. This topologically assisted optimization contains two steps. First, a global evolutionary optimization is performed for the shape parameters, and then a topological analysis reveals the local and global extrema of the objective function directly from the data. This non-dimensional objective function compares the achieved thrust with the required torque. Rotor blades have a decisive contribution to the performance of quadcopters. A two-blade rotor with pre-defined chord length distribution is chosen as the baseline model. The simulation is performed in a moving reference frame with a k − ω turbulence model for the hovering condition. The rotor shape is parameterized by the twist angle distribution. The optimization of this distribution employs a genetic algorithm. The local maxima are distilled from the data using a novel topological analysis inspired by discrete scalar-field topology. We identify one global maximum to be located in the interior of the data and five further local maxima related to errors from non-converged simulations. The interior location of the global optimum suggests that small improvements can be gained from further optimization. The local maxima have a small persistence, i.e., disappear under a small ε perturbation of the figure of merit values. In other words, the data may be approximated by a smooth mono-modal surrogate model. Thus, the topological data analysis provides valuable insight for optimization and surrogate modeling. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ROTORS
*STRUCTURAL optimization
*GLOBAL optimization
Subjects
Details
- Language :
- English
- ISSN :
- 10706631
- Volume :
- 35
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Physics of Fluids
- Publication Type :
- Academic Journal
- Accession number :
- 164088345
- Full Text :
- https://doi.org/10.1063/5.0145941